Method and apparatus for implementing space time processing

ABSTRACT

A method and apparatus for implementing spatial processing with unequal modulation and coding schemes (MCSs) or stream-dependent MCSs are disclosed. Input data may be parsed into a plurality of data streams, and spatial processing is performed on the data streams to generate a plurality of spatial streams. An MCS for each data stream is selected independently. The spatial streams are transmitted via multiple transmit antennas. At least one of the techniques of space time block coding (STBC), space frequency block coding (SFBC), quasi-orthogonal Alamouti coding, time reversed space time block coding, linear spatial processing and cyclic delay diversity (CDD) may be performed on the data/spatial streams. An antennal mapping matrix may then be applied to the spatial streams. The spatial streams are transmitted via multiple transmit antennas. The MCS for each data stream may be determined based on a signal-to-noise ratio of each spatial stream associated with the data stream.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.14/599,651 filed Jan. 19, 2015, which issued as U.S. Pat. No. 9,621,251on Apr. 11, 2017, which is a continuation of U.S. patent applicationSer. No. 13/651,901 filed Oct. 15, 2012, which issued as U.S. Pat. No.8,971,442 on Mar. 3, 2015, which is a continuation of U.S. patentapplication Ser. No. 11/621,755 filed Jan. 10, 2007, which issued asU.S. Pat. No. 8,295,401 on Oct. 23, 2012, which claims benefit of U.S.Provisional Application No. 60/758,034 filed Jan. 11, 2006, which isincorporated by reference as if fully set forth.

FIELD OF INVENTION

The present invention is related to wireless communication systems. Moreparticularly, the present invention is related to a method and apparatusfor implementing spatial processing with unequal modulation and codingschemes (MCSs).

BACKGROUND

The IEEE 802.11n joint proposal group currently proposes using a hybridspace-time block cede (STBC) and spatial division multiplexing (SDM)scheme for the next generation of high performance wireless networks.This hybrid STBC/SDM scheme results in unbalanced quality of service fordata streams which translates into lower residual signal-to-noise ratio(SNR) at the output of a receiver. In conventional systems, equal MCSsare applied to all spatial streams. However, this results in a loss ofbenefits of the diversity gain for the spatial stream carried by STBCprecoding.

Therefore, it would be desirable to provide a method and apparatus forapplying unequal MCSs or stream dependent MCSs while performing spatialprocessing, such as STBC.

SUMMARY

The present invention is related to a method and apparatus forimplementing spatial processing with unequal MCSs or stream-dependentMCSs. Input data may be parsed into a plurality of data streams, andspatial processing is performed on the data streams to generate aplurality of spatial streams. An MCS for each data stream is selectedindependently. The spatial streams are then transmitted via multipletransmit antennas. At least one of the techniques of STBC, spacefrequency block coding (SFBC), quasi-orthogonal Alamouti coding, timereversed space time block coding, linear spatial processing and cyclicdelay diversity (CDD) may be performed on the data/spatial streams. Anantenna mapping matrix may then be applied to the spatial streams. Theresulted spatial streams are then transmitted via multiple transmitantennas. The MCS for each data stream may be determined based on an SNRof each spatial stream associated with the data stream.

BRIEF DESCRIPTION OF THE DRAWINGS

A more detailed understanding of the invention may be had from thefollowing description of a preferred embodiment, given by way of exampleand to be understood in conjunction with the accompanying drawingswherein:

FIG. 1 is a block diagram of a transmitter configured in accordance withthe present invention;

FIG. 2 a block diagram of a receiver configured in accordance with thepresent invention;

FIG. 3 is a block diagram of an exemplary spatial processing unitconfigured to perform STBC and/or linear spatial mapping; and

FIGS. 4 and 5 show simulation results for IEEE 802.11n, channels E and Busing a 3×2 antenna configuration and a linear minimum mean square error(LMMSE) receiver.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

In accordance with the present invention, unequal MCSs orstream-dependent MCSs are applied to different spatial streams. Thepresent invention may be applied in an orthogonal frequency divisionmultiplexing (OFDM)-multiple-input multiple-output (MIMO) system, amulti-carrier code division multiple access (MC-CDMA) system, a CDMAsystem, or the like. Unequal MCSs are applied in different data streamsto take advantage of unequal SNRs for different data streams. Forexample, a higher order MCS may be applied to a spatial stream which hasdiversity coding and a lower order MCS to a spatial stream that does nothave diversity coding to reduce the total self induced interference.With unequal MCSs, or stream-dependent MCSs, a simpler receiveralgorithm, (e.g., linear minimum mean square error (LMMSE)), may be useddue to the reduced self interference.

FIG. 1 is a block diagram of a transmitter 100 configured in accordancewith the present invention. The transmitter 100 includes a channelencoder 102, a rate matching unit 104, a spatial parser 106, a pluralityof interleavers 108 a-108 n _(ss), a plurality of constellation mappers110 a-110 n _(ss), a plurality of multiplexers 116 a-116 n _(ss), aspatial processing unit 120, a plurality of inverse fast Fouriertransform (IFFT) units 122 a-122 n _(tx), a plurality of cyclic prefix(CP) insertion units 124 a-124 n _(tx) and a plurality of transmitantennas 126 a-126 n _(tx). It, should be noted that the configurationshown in FIG. 1 is provided as an example, not as a limitation, and theprocessing performed by the components may be implemented by more orless components and the order of processing may be changed.

The channel encoder 102 encodes input data 101. Adaptive modulation andcoding (AMC) is used and any coding rate and any coding scheme may beused. For example, the coding rate may be ½, ⅓, ⅕, ¾, or the like. Thecoding scheme may be Turbo coding, convolutional coding, block coding,low density parity check (LDPC) coding, or the like. The encoded data103 may be punctured by the rate matching unit 104.

The encoded data after rate matching 105 is parsed into a plurality of(N_(SS)) spatial streams 107 a-107 n _(ss) by the spatial parser 106.Data bits on each data stream 107 a-107 n _(ss) are preferablyinterleaved by the interleaves 108 a-108 n _(ss). The data bits afterinterleaving 109 a-109 n _(ss) are then mapped to symbols 111 a-111 n_(ss) by the constellation mappers 110 a-110 n _(ss) in accordance witha selected modulation scheme. The modulation scheme may be Quadraturephase shift keying (QPSK), 8PSK, 16 Quadrature amplitude modulation(QAM), 64 QAM, or the like. Control data 112 a-112 n _(ss) and/or pilots114 a-114 n _(ss) are multiplexed with symbols 111 a-111 n _(ss) by themultiplexer 116 a-116 n _(ss). The symbols 117 a-117 n _(ss) (includingthe multiplexed control data 112 a-112 n _(ss) and/or pilots 114 a-114 n_(ss) are processed by the spatial processing unit 120.

Alternatively, the input data 101 may be split prior to channel encodingand the split multiple input data may be encoded by two or more separateencoders. Alternatively, instead of, or in addition to, parsing one datastream into multiple data streams, several input data streams that, maybelong to one or more users may be processed to be transmitted viaseveral spatial streams.

The spatial processing unit 120 selectively performs spatial processingon the symbols 117 a-117 n _(ss) based on channel state information 118and outputs N_(TX) data streams 121 a-121 n _(tx). The spatialprocessing may be space time coding (STC), spatial multiplexing (SM),linear spatial mapping, or transmit beamforming. For STC, any form ofSTC may be used including STBC, SFBC, quasi-orthogonal Alamouti for four(4) transmit antennas, time reversed STBC (TR-STBC), CDD, or the like.

The channel state information 118 may be at least one of a V matrix forevery sub-carrier, an SNR, a channel matrix rank, a channel conditionnumber, delay spread, or short and/or long term channel statistics. TheV matrix is an unitary matrix obtained from the singular valuedecomposition (SVD) of the estimated channel matrix. The channelcondition number is related to the rank of the channel matrix. Anill-conditioned channel may be rank deficient. A low rank, orill-conditioned channel would exhibit better robustness using adiversity scheme such STBC since the channel would not have sufficientdegree of freedom to support SM with transmit beamforming. A high rankchannel would support higher data rates using SM with transmitbeamforming. The channel state information 118 may be obtained usingconventional techniques, such as direct channel feedback (DCFB).

The data streams 121 a-121 n _(tx) from the spatial processing unit 120are processed by the IFFT units 122 a-122 n _(tx) which output timedomain data 123 a-123 n _(tx). A CP is added to each of the time domaindata 123 a-123 n _(tx) by the CP insertion unit 124 a-124 n _(tx). Thetime domain data with CP 125 a-125 n _(tx) is then transmitted via thetransmit antennas 126 a-126 n _(tx).

FIG. 2 is a block diagram of a receiver 200 configured in accordancewith the present invention. The receiver 200 comprises a plurality ofreceive antennas 202 a-202 n _(rx), a channel estimator 204, a noiseestimator 206, a channel correlation matrix calculator 208, an SNR normconstant calculator 210, a plurality of OFDM processing units 212 a-212n _(rx), a spatial decoder 214, a plurality of constellation de-mappers126 a-126 n _(ss), a plurality of SNR normalization units 128 a-128 n_(ss), a plurality of de-interleavers 220 a-220 n _(ss), a spatialde-parser 222 and a decoder 224. It should be noted that theconfiguration shown in FIG. 2 is provided as an example, not as alimitation, and the processing performed by the components may beimplemented by more or less components and the order of processing maybe changed.

A plurality of received data streams 203 a-203 n _(rx) are input intothe channel estimator 204, the noise estimator 206 and the OFDMprocessing units 212 a-212 n _(rx). The channel estimator 204 performschannel estimate to generate a channel matrix 205 using a conventionalmethod. The noise estimator 206 calculates a noise variance 207. Thechannel correlation matrix calculator 208 generates a correlation matrix209 from the channel matrix 205, which will be explained in detailhereinafter. The SNR norm constant calculator 210 calculates SNR normconstants 211 a-211 n _(ss) from the correlation matrix 209 and thenoise variance 207, which will be explained, in detail hereinafter.

Each of the OFDM processing unit 212 a-212 n _(rx) removes a CP fromeach received data stream 203 a-203 n _(rx) and performs a fast Fouriertransform (FFT) to output frequency domain data 212 a-212 n _(rx). Theoutputs 212 a-212 n _(rx) from the OFDM processing units 212 a-212 n_(rx) are processed by the spatial decoder 214. The spatial decoder 214may be a minimum mean square error (MMSE) decoder, an MMSE-successiveinterference cancellation (SIC) decoder or a maximum likelihood (ML)decoder.

After spatial decoding, the decoded data 215 a-212 n _(ss) is processedby the constellation de-mappers 216 a-216 n _(ss) to generate bitstreams 217 a-217 n _(ss). The bit streams 217 a-217 n _(ss) arenormalized by the SNR normalization units 218 a-218 n _(ss) based on theSNR norm constants 211 a-211 n _(ss). The normalized bits streams 219a-219 n _(ss) are then processed by the de-interleavers 220 a-220 n_(ss). The de-interleaved bits 221 a-221 n _(ss) are merged into one bitstream 223 by the spatial de-parser 222. The bit stream 223 is thenprocessed by the decoder 224 to recover the input data 225.

Hereinafter, spatial processing at the transmitter 100 and the receiver200 will be explained with reference to STBC as a representativeexample. The following definitions will be used:

N_(TX): the number of transmit antennas;

N_(SS): the number of spatial streams;

N_(STS): the number of streams after STBC;

d_(k,n): a data vector at symbol time n;

s_(k,n): a vector after STBC at symbol time n;

x_(k,n): a vector after P matrix, in FIG. 3 at symbol time n; and

y_(k,n): a received vector at symbol time n.

FIG. 3 is a block diagram of an exemplary spatial processing unit 120configured to perform STBC and/or linear spatial mapping. The spatialprocessing unit 120 may include an STBC unit 302, a CDD unit 304 and anantenna mapping unit 306. Each of the symbols 117 a-117 n _(ss) is astream of complex numbers. A complex symbol transmitted on a spatialstream i of a subcarrier k of an OFDM symbol n is denoted by d_(k,i,n).The STBC unit 302 processes two sequential OFDM symbols in eachsubcarrier. The output symbols from the STBC unit 302 on an outputspace-time stream i_(STS) on a subcarrier k on OFDM symbols 2m and 2m+1are given by:s _(k,i) _(XTS) _(,2m) =f _(0,i) _(STS) (d _(k,i) _(XS) _(,2m) ,d _(k,i)_(SS) _(,2m+1))s _(k,i) _(STS) _(,2m+1) =f _(1,i) _(STS) (D _(k,i) _(XS) _(,2m) ,d_(k,i) _(SS) _(,2m+1)),  Equation (1)where f_(0,i) _(STS) and f_(1,i) _(STS) are defined in Table 1.

TABLE 1 N_(STS) N_(SS) i_(STS) f_(0, i) _(STS) f_(1, i) _(STS) 2 1 1d_(k, 1, 2m) d_(k, 1, 2m+1) 2 −d_(k, 1, 2m+1)* d_(k, 1, 2m)* 3 2 1d_(k, 1, 2m) d_(k, 1, 2m+1) 2 −d_(k, 1, 2m+1)* d_(k, 1, 2m)* 3d_(k, 2, 2m) d_(k, 2, 2m+1) 4 2 1 d_(k, 1, 2m) d_(k, 1, 2m+1) 2−d_(k, 1, 2 m+1)* d_(k, 1, 2m)* 3 d_(k, 2, 2m) d_(k, 2, 2m+1) 4−d_(k, 2, 2m+1)* d_(k, 2, 2m)* 3 1 d_(k, 1, 2m) d_(k, 1, 2m+1) 2−d_(k, 1, 2, m+1)* d_(k, 1, 2m)* 3 d_(k, 2, 2m) d_(k, 2, 2m+1) 4d_(k, 3, 2m) d_(k, 3, 2m+1)

Linear spatial processing may be performed by the CDD unit 304 and theantenna mapping unit 306 on the output symbols from the STBC unit 302.If STBC is not performed, s_(k,i,n)=d_(k,i,n) and N_(STS)=N_(SS). Linearspatial processing is defined as a sequence of rotations of the vectorof symbols that is to be transmitted M a given subcarrier. Theprocessing by the CDD unit 304 and the antenna mapping unit 306 areexpressed as follows:x _(k,n) =[P _(map)(k)]_(N) _(STS) C _(CDD)(k))s _(k,n),  Equation (2)where s_(k,n)=[s_(k,i,n) . . . s_(k,N) _(STS) _(,N)]^(T) is anN_(STS)-vector of modulation symbols to be transmitted on a subcarrier kof an OFDM symbol n. C_(CDD)(k) is an N_(SS)×N_(SS) diagonal cyclicdelay matrix which represents the cyclic delay in the frequency domain.The diagonal values are given by [C_(CDD)(k)]_(i,i)=exp(−j2πkΔ_(P)T_(CS)^(i)). [P_(map)(k)]_(N) _(STS) is an N_(TX)×N_(STS) matrix comprisingthe first N_(STS) columns of the N_(TX)×N_(TX) unitary antenna mappingmatrix P_(map)(k). This may be an identity matrix for direct-mappedoperation, a mapping matrix for spatial spreading operation, or achannel-specific steering matrix such as a set of channel eigenvectors,x_(k,n) is an N_(TX)-vector of transmitted symbols in a subcarrier k ofan OFDM symbol n.

A channel matrix H_(eff) is an effective channel seen y the vectors_(k,n) so that:y _(k,n) =H _(eff) s _(k,n) +n _(k,n).  Equation (3)

In the receiver, y_(k,2m) and y*_(k,2m+1) are combined into a singlevector as follows:

$\begin{matrix}{y_{k} = {\begin{bmatrix}y_{k,{2m}} \\y_{k,{{2m} + 1}}^{*}\end{bmatrix}.}} & {{Equation}\mspace{14mu}(4)}\end{matrix}$

Using Equations (3) and (4),

$\begin{matrix}{y_{k} = {\begin{bmatrix}{H_{eff}s_{k,{2m}}} \\{H_{eff}^{*}s_{k,{{2m} + 1}}^{*}}\end{bmatrix} + {\begin{bmatrix}n_{k,{2m}} \\n_{k,{{2m} + 1}}^{*}\end{bmatrix}.}}} & {{Equation}\mspace{14mu}(5)}\end{matrix}$

In the vectors s_(k,2m) and s*_(k,2m+1), any data value that appears ineither of them will appear either conjugated in both or unconjugated inboth. This allows writing Equation (5) as a simple matrix form, asillustrated by the following specific example.

Consider the case of N_(tx)=3 and N_(ss)=2, (i.e., two (2) spatialstreams are generated from input data by the spatial parser 106 andthree data streams are generated from the spatial processing unit 120 atthe transmitter 100). One of the three data streams is created from themodified replica of one data stream of the spatial parser 106 fortransmit diversity as shown below.

From Table 1, for the case of N_(tx)=3 and N_(ss)2, the following can beseen:s _(k,1,2m) =d _(k,1,2m);s _(k,2,2m) =−d* _(k,1,2m+1); ands _(k,3,2m) =d _(k,2,2m).so that

$\begin{matrix}{s_{k,{2m}} = {\begin{bmatrix}d_{k,1,{2m}} \\{- d_{k,1,{{2m} + 1}}^{*}} \\d_{k,2,{2m}}\end{bmatrix}.}} & {{Equation}\mspace{14mu}(6)}\end{matrix}$

Also,s _(k,1,2m+1) =d _(k,1,2m+1);s _(k,2,2m+1) =d* _(k,1,2m); ands _(k,3,2m+1) =d _(k,2,2m+1).so that

$\begin{matrix}{{s_{k,{{2m} + 1}} = \begin{bmatrix}d_{k,1,{{2m} + 1}} \\d_{k,1,{2m}}^{*} \\d_{k,2,{{2m} + 1}}\end{bmatrix}};} & {{Equation}\mspace{14mu}(7)}\end{matrix}$and

$\begin{matrix}{s_{k,{{2m} + 1}}^{*} = {\begin{bmatrix}d_{k,1,{{2m} + 1}}^{*} \\d_{k,1,{2m}} \\d_{k,2,{{2m} + 1}}^{*}\end{bmatrix}.}} & {{Equation}\mspace{14mu}(8)}\end{matrix}$

Using Equations (6) and (8), Equation (5) can be rewritten as a standardmatrix equation involving the four data values d_(k,1,2m),d*_(k,1,2m+1), d_(k,2,2m), d*_(k,2,2m+1) as follows (the asterisks meanconjugation, not Hermitian conjugation).

$\begin{matrix}\begin{matrix}{y_{k} = \left\lbrack {\left. \quad\begin{matrix}{H_{eff}\left( {\text{:},1} \right)} & {- {H_{eff}\left( {\text{:},2} \right)}} & {H_{eff}\left( {\text{:},3} \right)} & 0 \\{H_{eff}^{*}\left( {\text{:},2} \right)} & {H_{eff}^{*}\left( {\text{:},1} \right)} & 0 & {H_{eff}^{*}\left( {\text{:},3} \right)}\end{matrix} \right\rbrack{\quad{\left\lbrack \begin{matrix}d_{k,1,{2m}} \\d_{k,1,{{2m} + 1}}^{*} \\d_{k,2,{2m}} \\d_{k,2,{{2m} + 1}}^{*}\end{matrix} \right\rbrack + {\quad{\begin{bmatrix}n_{k,{2m}} \\n_{k,{{2m} + 1}}^{*}\end{bmatrix}.}}}}} \right.} & \;\end{matrix} & {{Equation}\mspace{20mu}(9)}\end{matrix}$

This is now in a standard MIMO form, but with a channel matrix which isa composite of the various columns of H_(eff). The receiver 200demodulates the data vector d:

$\begin{matrix}{d = {\left\lbrack \begin{matrix}d_{k,1,{2m}} \\d_{k,1,{{2m} + 1}}^{*} \\d_{k,2,{2m}} \\d_{k,2,{{2m} + 1}}^{*}\end{matrix} \right\rbrack.}} & {{Equation}\mspace{14mu}(10)}\end{matrix}$

An MMSE demodulator may be used for the data vector in Equation (10).Let the channel matrix in Equation (9) be denoted as follows:

$\begin{matrix}{\overset{\sim}{H} = \left\lbrack {\left. \quad\begin{matrix}{H_{eff}\left( {\text{:},1} \right)} & {- {H_{eff}\left( {\text{:},2} \right)}} & {H_{eff}\left( {\text{:},3} \right)} & 0 \\{H_{eff}^{*}\left( {\text{:},2} \right)} & {H_{eff}^{*}\left( {\text{:},1} \right)} & 0 & {H_{eff}^{*}\left( {\text{:},3} \right)}\end{matrix} \right\rbrack.} \right.} & {{Equation}\mspace{14mu}(11)}\end{matrix}$

An MMSE solution is as follows (dropping the index k and using thesymbol ‘+’ for Hermitian conjugate):

$\begin{matrix}{{\hat{d} = {\left( {{\frac{1}{\sigma_{d}^{2}}I} + {\frac{1}{\sigma_{n}^{2}}{\overset{\sim}{H}}^{+}\overset{\sim}{H}}} \right)^{- 1}{\overset{\sim}{H}}^{+}\frac{1}{\sigma_{n}^{2}}y}};} & {{Equation}\mspace{14mu}(12)}\end{matrix}$or, equivalently,

$\begin{matrix}{\hat{d} = {\left( {{\frac{\sigma_{n}^{2}}{\sigma_{d}^{2}}I} + {{\overset{\sim}{H}}^{+}\overset{\sim}{H}}} \right)^{- 1}{\overset{\sim}{H}}^{+}{y.}}} & {{Equation}\mspace{14mu}(13)}\end{matrix}$

Equation (9) can be written as follows:y={tilde over (H)}d+n.  Equation (14)Substituting Equation (14) into Equation (12) yields:

$\begin{matrix}{\hat{d} = {{\left( {{\frac{\sigma_{n}^{2}}{\sigma_{d}^{2}}I} + {{\overset{\sim}{H}}^{+}\overset{\sim}{H}}} \right)^{- 1}{\overset{\sim}{H}}^{+}\overset{\sim}{H}d} + {\left( {{\frac{\sigma_{n}^{2}}{\sigma_{d}^{2}}I} + {{\overset{\sim}{H}}^{+}\overset{\sim}{H}}} \right)^{- 1}{\overset{\sim}{H}}^{+}{n.}}}} & {{Equation}\mspace{14mu}(15)}\end{matrix}$

Using Equation (11), the correlation matrix {tilde over (H)}⁺ {tildeover (H)} becomes as follows:

$\begin{matrix}{{{\overset{\sim}{H}}^{+}\overset{\sim}{H}} = {\begin{bmatrix}{H_{eff}^{+}\left( {\text{:},1} \right)} & {H_{eff}^{T}\left( {\text{:},2} \right)} \\{- {H_{eff}^{+}\left( {\text{:},2} \right)}} & {H_{eff}^{T}\left( {\text{:},1} \right)} \\{H_{eff}^{+}\left( {\text{:},3} \right)} & 0 \\0 & {H_{eff}^{T}\left( {\text{:},3} \right)}\end{bmatrix}{\quad\left\lbrack {\left. \quad\begin{matrix}{H_{eff}\left( {\text{:},1} \right)} & {- {H_{eff}\left( {\text{:},2} \right)}} & {H_{eff}\left( {\text{:},3} \right)} & 0 \\{H_{eff}^{*}\left( {\text{:},2} \right)} & {H_{eff}^{*}\left( {\text{:},1} \right)} & 0 & {H_{eff}^{*}\left( {\text{:},3} \right)}\end{matrix} \right\rbrack\begin{matrix}{{{\overset{\sim}{H}}^{+}\overset{\sim}{H}} = \left\lbrack \begin{matrix}{{{H_{eff}\left( {\text{:},1} \right)}}^{2} + {{H_{eff}\left( {\text{:},2} \right)}}^{2}} \\0 \\{{H_{eff}^{+}\left( {\text{:},3} \right)}{H_{eff}\left( {\text{:},1} \right)}} \\{{H_{eff}^{+}\left( {\text{:},2} \right)}{H_{eff}\left( {\text{:},3} \right)}}\end{matrix} \right.} & {\begin{matrix}0 \\{{{H_{eff}\left( {\text{:},1} \right)}}^{2} + {{H_{eff}\left( {\text{:},2} \right)}}^{2}} \\{{- {H_{eff}^{+}\left( {\text{:},3} \right)}}{H_{eff}\left( {\text{:},2} \right)}} \\{{H_{eff}^{+}\left( {\text{:},1} \right)}{H_{eff}\left( {\text{:},3} \right)}}\end{matrix}} & {\begin{matrix}{{H_{eff}^{+}\left( {\text{:},1} \right)}{H_{eff}\left( {\text{:},3} \right)}} \\{{- {H_{eff}^{+}\left( {\text{:},2} \right)}}{H_{eff}\left( {\text{:},3} \right)}} \\{{H_{eff}\left( {\text{:},3} \right)}}^{2} \\0\end{matrix}} & \left. \begin{matrix}{{H_{eff}^{+}\left( {\text{:},3} \right)}{H_{eff}\left( {\text{:},2} \right)}} \\{{H_{eff}^{+}\left( {\text{:},3} \right)}{H_{eff}\left( {\text{:},1} \right)}} \\0 \\{{H_{eff}\left( {\text{:},3} \right)}}^{2}\end{matrix} \right\rbrack\end{matrix}} \right.}}} & {{Equation}\mspace{14mu}(16)}\end{matrix}$

The effective SNR for the k^(th) data stream in Equation (9), after MMSEreceiver processing, is known to be:

$\begin{matrix}{{{SNR}_{k} = {\frac{1}{\left( {I + {\rho{\overset{\sim}{H}}^{+}\overset{\sim}{H}}} \right)_{kk}^{- 1}} - 1}};{{{where}\mspace{14mu}\rho} = {\frac{\sigma_{d}^{2}}{\sigma_{n}^{2}}.}}} & {{Equation}\mspace{14mu}(17)}\end{matrix}$

For high SNR, Equation (17) becomes:

$\begin{matrix}{{SNR}_{k} \approx {\frac{\rho}{\left( {{\overset{\sim}{H}}^{+}\overset{\sim}{H}} \right)_{kk}^{- 1}}.}} & {{Equation}\mspace{14mu}(18)}\end{matrix}$

The matrix {tilde over (H)}⁺ {tilde over (H)} has the form:

$\begin{matrix}{{{\overset{\sim}{H}}^{+}\overset{\sim}{H}} = {\begin{bmatrix}x & 0 & a & b \\0 & x & {- b^{*}} & a^{*} \\a^{*} & {- b} & z & 0 \\b^{*} & a & 0 & z\end{bmatrix}.}} & {{Equation}\mspace{14mu}(19)}\end{matrix}$

The definitions of the parameters in Equation (19) are easily found fromthe expression for {tilde over (H)}⁺ {tilde over (H)}. Using the generalformula for the inverse of a matrix as follows:

$\begin{matrix}{{A^{- 1} = \frac{{cof}^{\; T}(A)}{\det\;(A)}};} & {{Equation}\mspace{14mu}(20)}\end{matrix}$

It can be shown that the diagonal elements ({tilde over (H)}⁺ {tildeover (H)})⁻¹ are given by:

$\begin{matrix}{{\left( {{\overset{\sim}{H}}^{+}\overset{\sim}{H}} \right)_{11}^{- 1} = \frac{z\left( {{xz} - {b}^{2} - {a}^{2}} \right)}{\det\left( {{\overset{\sim}{H}}^{+}\overset{\sim}{H}} \right)}};} & {{Equation}\mspace{14mu}(21)} \\{{\left( {{\overset{\sim}{H}}^{+}\overset{\sim}{H}} \right)_{22}^{- 1} = \frac{z\left( {{xz} - {b}^{2} - {a}^{2}} \right)}{\det\left( {{\overset{\sim}{H}}^{+}\overset{\sim}{H}} \right)}};} & {{Equation}\mspace{14mu}(22)} \\{{{\left( {{\overset{\sim}{H}}^{+}\overset{\sim}{H}} \right)_{33}^{- 1} = \frac{x\left( {{xz} - {b}^{2} - {a}^{2}} \right)}{\det\left( {{\overset{\sim}{H}}^{+}\overset{\sim}{H}} \right)}};{and}}\mspace{14mu}} & {{Equation}\mspace{14mu}(23)} \\{\left( {{\overset{\sim}{H}}^{+}\overset{\sim}{H}} \right)_{44}^{- 1} = {\frac{x\left( {{xz} - {b}^{2} - {a}^{2}} \right)}{\det\left( {{\overset{\sim}{H}}^{+}\overset{\sim}{H}} \right)}.}} & {{Equation}\mspace{14mu}(24)}\end{matrix}$

Using Equation (18), SNRs the each data streams are obtained as follows:

$\begin{matrix}{{{SNR}_{1} = {\rho\frac{\det\left( {{\overset{\sim}{H}}^{+}\overset{\sim}{H}} \right)}{z\left( {{xz} - {b}^{2} - {a}^{2}} \right)}}};} & {{Equation}\mspace{14mu}(25)} \\{{{SNR}_{2} = {\rho\frac{\det\left( {{\overset{\sim}{H}}^{+}\overset{\sim}{H}} \right)}{z\left( {{xz} - {b}^{2} - {a}^{2}} \right)}}};} & {{Equation}\mspace{14mu}(26)} \\{{{SNR}_{3} = {\rho\frac{\det\left( {{\overset{\sim}{H}}^{+}\overset{\sim}{H}} \right)}{x\left( {{xz} - {b}^{2} - {a}^{2}} \right)}}};{and}} & {{Equation}\mspace{14mu}(27)} \\{{SNR}_{4} = {\rho{\frac{\det\left( {{\overset{\sim}{H}}^{+}\overset{\sim}{H}} \right)}{x\left( {{xz} - {b}^{2} - {a}^{2}} \right)}.}}} & {{Equation}\mspace{14mu}(28)}\end{matrix}$

For any above channel realization, the first two components d (the oneswhich have the STBC code applied to them) have the same SNR, and theother two have also equal SNR. The second one is generally smaller thanthe first one. The ratio of the SNRs for the coded to the uncodedcomponents of d is as follows;

$\begin{matrix}{\frac{{SNR}_{1,2}}{{SNR}_{3,4}} = {\frac{x}{z} = {\frac{{{H_{eff}\left( {:{,1}} \right)}}^{2} + {{H_{eff}\left( {:{,2}} \right)}}^{2}}{{{H_{eff}\left( {:{,3}} \right)}}^{2}}.}}} & {{Equation}\mspace{14mu}(29)}\end{matrix}$Assuming that the three columns of H_(eff) have similar properties, theSNR will be about 3 dB higher on average for the TEC coded symbols.

In implementing STBC, a pair of subsequent symbols may be transmittedvia a same frequency or different frequencies. For evaluation, thesimplest case of N_(tx)=2 and N_(ss)=1 is considered herein supposingthat there is only one receive antenna at the receiver. The effectivechannel matrix is represented as a 1×2 matrix as follows;H _(eff) =[h ₁ h ₂],  Equation (30)and the data vector becomes as follows:

$\begin{matrix}{d = {\begin{bmatrix}d_{k,1,{2\; m}} \\d_{k,1,{{2\; m} + 1}}^{*}\end{bmatrix}.}} & {{Equation}\mspace{14mu}(31)}\end{matrix}$

When the same frequency is used for the successive symbols, H_(eff) isthe same for both symbols and Equation (5) becomes as follows:

$\begin{matrix}{y_{k} = {{\begin{bmatrix}h_{1} & {- h_{2}} \\h_{2}^{*} & h_{1}^{*}\end{bmatrix}\begin{bmatrix}d_{k,1,{2\; m}} \\d_{k,1,{{2\; m} + 1}}^{*}\end{bmatrix}} + {\begin{bmatrix}n_{k,{2\; m}} \\n_{k,{{2\; m} + 1}}^{*}\end{bmatrix}.}}} & {{Equation}\mspace{14mu}(32)}\end{matrix}$

If a zero forcing receiver is used, the first step is to multiply y_(k)the Hermitian conjugate of the channel matrix:

$\begin{matrix}{\mspace{79mu}{{{\overset{\sim}{H} = \begin{bmatrix}h_{1} & {- h_{2}} \\h_{2}^{*} & h_{1}^{*}\end{bmatrix}};}\mspace{20mu}{{to}\mspace{14mu}{get}}\begin{matrix}{{{\overset{\sim}{H}}^{+}y_{k}} = {{{\begin{bmatrix}h_{1}^{*} & h_{2} \\{- h_{2}^{*}} & h_{1}\end{bmatrix}\begin{bmatrix}h_{1} & {- h_{2}} \\h_{2}^{*} & h_{1}^{*}\end{bmatrix}}\begin{bmatrix}d_{k,1,{2\; m}} \\d_{k,1,{{2\; m} + 1}}^{*}\end{bmatrix}} + {\begin{bmatrix}h_{1}^{*} & h_{2} \\{- h_{2}^{*}} & h_{1}\end{bmatrix}\begin{bmatrix}n_{k,{2\; m}} \\n_{k,{{2\; m} + 1}}^{*}\end{bmatrix}}}} \\{= {{\begin{bmatrix}{{h_{1}}^{2} + {h_{2}}^{2}} & 0 \\0 & {{h_{1}}^{2} + {h_{2}}^{2}}\end{bmatrix}\begin{bmatrix}d_{k,1,{2\; m}} \\d_{k,1,{{2\; m} + 1}}^{*}\end{bmatrix}} + {{\begin{bmatrix}h_{1}^{*} & h_{2} \\{- h_{2}^{*}} & h_{1}\end{bmatrix}\begin{bmatrix}n_{k,{2\; m}} \\n_{k,{{2\; m} + 1}}^{*}\end{bmatrix}}.}}}\end{matrix}}} & {{Equation}\mspace{14mu}(33)}\end{matrix}$

The diagonal matrix elements |h₁|²+|h₂|² in the signal part representthe diversity of order 2 that is gained by the STBC code.

When different frequencies are used fir the successive symbols, theeffective channels for the two symbols are as follows:H _(eff) =[h ₁ h ₂] for the first symbol; andH _(eff) =[g ₁ g ₂] for the second symbol.

In this case the modified Equation (5) be as follows:

$\begin{matrix}{{y_{k} = {{\begin{bmatrix}h_{1} & {- h_{2}} \\g_{2}^{*} & g_{1}^{*}\end{bmatrix}\begin{bmatrix}d_{k,1,{2\; m}} \\d_{k,1,{{2\; m} + 1}}^{*}\end{bmatrix}} + \begin{bmatrix}n_{k,{2\; m}} \\n_{k,{{2\; m} + 1}}^{*}\end{bmatrix}}};} & {{Equation}\mspace{14mu}(34)}\end{matrix}$and the followings are obtained:

$\begin{matrix}{\mspace{79mu}{{{\overset{\sim}{H} = \begin{bmatrix}h_{1} & {- h_{2}} \\h_{2}^{*} & h_{1}^{*}\end{bmatrix}};}\mspace{20mu}{and}}} & {{Equation}\mspace{14mu}(35)} \\\begin{matrix}{{{\overset{\sim}{H}}^{+}y_{k}} = {{{\begin{bmatrix}h_{1}^{*} & g_{2} \\{- h_{2}^{*}} & g_{1}\end{bmatrix}\begin{bmatrix}h_{1} & {- h_{2}} \\g_{2}^{*} & g_{1}^{*}\end{bmatrix}}\begin{bmatrix}d_{k,1,{2\; m}} \\d_{k,1,{{2\; m} + 1}}^{*}\end{bmatrix}} +}} \\{\begin{bmatrix}h_{1}^{*} & g_{2} \\{- h_{2}^{*}} & g_{1}\end{bmatrix}\begin{bmatrix}n_{k,{2\; m}} \\n_{k,{{2\; m} + 1}}^{*}\end{bmatrix}} \\{= {{\begin{bmatrix}{{h_{1}}^{2} + {g_{2}}^{2}} & {{{- h_{1}^{*}}h_{2}} + {g_{1}^{*}g_{2}}} \\{{{- h_{2}^{*}}h_{1}} + {g_{2}^{*}g_{1}}} & {{h_{2}}^{2} + {g_{2}}^{2}}\end{bmatrix}\begin{bmatrix}d_{k,1,{2\; m}} \\d_{k,1,{{2\; m} + 1}}^{*}\end{bmatrix}} +}} \\{{\begin{bmatrix}h_{1}^{*} & g_{2} \\{- h_{2}^{*}} & g_{1}\end{bmatrix}\begin{bmatrix}n_{k,{2\; m}} \\n_{k,{{2\; m} + 1}}^{*}\end{bmatrix}}.}\end{matrix} & {{Equation}\mspace{14mu}(36)}\end{matrix}$

The diagonal matrix elements |h₁|²+|g₂|² in the signal part representthe diversity of order 2 that is gained by the STBC code. In this case,the diagonal elements still represent diversity of order 2. However, theof diagonal elements contribute interference i.e., non-orthogonality).

For the 2×1 case of Table 1, Equation (5) becomes as follows:

$\begin{matrix}{{{y_{k} = {{\begin{bmatrix}h_{1} & {- h_{2}} \\h_{2}^{*} & h_{1}^{*}\end{bmatrix}\begin{bmatrix}d_{k,1,{2\; m}} \\d_{k,1,{{2\; m} + 1}}^{*}\end{bmatrix}} + \begin{bmatrix}n_{k,{2\; m}} \\n_{k,{{2\; m} + 1}}^{*}\end{bmatrix}}};}{wherein}} & {{Equation}\mspace{14mu}(37)} \\{{{\overset{\sim}{H} = \begin{bmatrix}h_{1} & {- h_{2}} \\h_{2}^{*} & h_{1}^{*}\end{bmatrix}};}{and}} & {{Equation}\mspace{14mu}(38)} \\{{d = \begin{bmatrix}d_{k,1,{2\; m}} \\d_{k,1,{{2\; m} + 1}}^{*}\end{bmatrix}},} & {{Equation}\mspace{14mu}(39)}\end{matrix}$

The MMSE estimator of d in this case is as follows:{circumflex over (d)}=ρ{tilde over (H)} ⁺(ρ{tilde over (H)}{tilde over(H)} ⁺ +I)⁻¹ y _(k),  Equation (40)

$\begin{matrix}{{\overset{\sim}{H}{\overset{\sim}{H}}^{+}} = {{\begin{bmatrix}h_{1} & {- h_{2}} \\h_{2}^{*} & h_{1}^{*}\end{bmatrix}\begin{bmatrix}h_{1}^{*} & h_{2} \\{- h_{2}^{*}} & h_{1}\end{bmatrix}} = {\quad{\begin{bmatrix}{{h_{1}}^{2} + {h_{2}}^{2}} & 0 \\0 & {{h_{1}}^{2} + {h_{2}}^{2}}\end{bmatrix}.}}}} & {{Equation}\mspace{14mu}(41)}\end{matrix}$

Equation (40) becomes:

$\begin{matrix}{{{\hat{d} = {{{\rho\begin{bmatrix}h_{1}^{*} & h_{2} \\{- h_{2}^{*}} & h_{1}\end{bmatrix}}\begin{bmatrix}{{\rho\left( {{h_{1}}^{2} + {h_{2}}^{2}} \right)} + 1} & 0 \\0 & {{\rho\left( {{h_{1}}^{2} + {h_{2}}^{2}} \right)} + 1}\end{bmatrix}}^{- 1}y_{k}}};}\mspace{20mu}{{or},}} & {{Equation}\mspace{14mu}(42)} \\{\mspace{79mu}{\begin{bmatrix}{\hat{d}}_{2\; m} \\{\hat{d}}_{{2\; m} + 1}^{*}\end{bmatrix} = {{{\frac{\rho}{{\rho\left( {{h_{1}}^{2} + {h_{2}}^{2}} \right)} + 1}\begin{bmatrix}h_{1}^{*} & h_{2} \\{- h_{2}^{*}} & h_{1}\end{bmatrix}}\begin{bmatrix}y_{2\; m} \\y_{{2\; m} + 1}^{*}\end{bmatrix}}.}}} & {{Equation}\mspace{14mu}(43)}\end{matrix}$

Alternatively, the MMSE estimates of d_(2m) and d_(2m+1) may be foundusing just y_(2m) and then y_(2m+1) and then adding them up. Applyingthis scheme for the first symbol:

$\begin{matrix}{{y_{2\; m} = {{\begin{bmatrix}h_{1} & h_{2}\end{bmatrix}\begin{bmatrix}d_{2\; m} \\{- d_{{2\; m} + 1}^{*}}\end{bmatrix}} + n_{2\; m}}},} & {{Equation}\mspace{14mu}(44)}\end{matrix}$and the MMSE estimate of the data vector from the first symbol is:

$\begin{matrix}{{\begin{bmatrix}{\hat{d}}_{2\; m} \\{- {\hat{d}}_{{2\; m} + 1}^{*}}\end{bmatrix} = {{\rho\begin{bmatrix}h_{1}^{*} \\h_{2}^{*}\end{bmatrix}}\left( {{{\rho\begin{bmatrix}h_{1} & h_{2}\end{bmatrix}}\begin{bmatrix}h_{1}^{*} \\h_{2}^{*}\end{bmatrix}} + 1} \right)^{- 1}y_{2\; m}}},{or},} & {{Equation}\mspace{14mu}(45)} \\{\begin{bmatrix}{\hat{d}}_{2\; m} \\{- {\hat{d}}_{{2\; m} + 1}^{*}}\end{bmatrix} = {{\frac{\rho}{{\rho\left( {{h_{1}}^{2} + {h_{2}}^{2}} \right)} + 1}\begin{bmatrix}h_{1}^{*} \\h_{2}^{*}\end{bmatrix}}{y_{2\; m}.}}} & {{Equation}\mspace{14mu}(46)}\end{matrix}$

Applying this scheme for the second symbol:

$\begin{matrix}{{y_{{2\; m} + 1} = {{\begin{bmatrix}h_{1} & h_{2}\end{bmatrix}\begin{bmatrix}d_{{2\; m} + 1} \\d_{2\; m}^{*}\end{bmatrix}} + n_{{2\; m} + 1}}},} & {{Equation}\mspace{14mu}(47)}\end{matrix}$and the MMSE estimate a the data vector from the second symbol is:

$\begin{matrix}{{\begin{bmatrix}{\hat{d}}_{{2\; m} + 1} \\{\hat{d}}_{2\; m}^{*}\end{bmatrix} = {{\rho\begin{bmatrix}h_{1}^{*} \\h_{2}^{*}\end{bmatrix}}\left( {{{\rho\begin{bmatrix}h_{1} & h_{2}\end{bmatrix}}\begin{bmatrix}h_{1}^{*} \\h_{2}^{*}\end{bmatrix}} + 1} \right)^{- 1}y_{{2\; m} + 1}}},{or},} & {{Equation}\mspace{14mu}(48)} \\{\begin{bmatrix}{\hat{d}}_{{2\; m} + 1} \\{\hat{d}}_{2\; m}^{*}\end{bmatrix} = {{\frac{\rho}{{\rho\left( {{h_{1}}^{2} + {h_{2}}^{2}} \right)} + 1}\begin{bmatrix}h_{1}^{*} \\h_{2}^{*}\end{bmatrix}}{y_{{2\; m} + 1}.}}} & {{Equation}\mspace{14mu}(49)}\end{matrix}$

Using Equations (47) and (49), the two estimates of d_(2m) are added upas follows:

$\begin{matrix}{{\hat{d}}_{2\; m} = {{\frac{\rho}{{\rho\left( {{h_{1}}^{2} + {h_{2}}^{2}} \right)} + 1}\left\lbrack {{h_{1}^{*}y_{2\; m}} + {h_{2}y_{{2\; m} + 1}^{*}}} \right\rbrack}.}} & {{Equation}\mspace{14mu}(50)}\end{matrix}$

The result is same to the result obtained in Equation (43). Doing thesum for the estimate of d_(2m+1) will also result in the same as thatfrom Equation (43). Thus, in the simple 2×1 Alamouti scheme, the twodecoding techniques are identical. However, it may not be as in the 3×2case in Table 1.

FIGS. 4 and 5 show simulation results for an IEEE 802.11n channels E andB using a 3×2 antenna configuration and a linear MMSE (LMMSE) receiver.The simulation results show that the case using an unequal modulationscheme of 64 QAM and QPSK has about 1.5 dB (0.8 dB) better in terms ofpacket error rate (PER) than the case using equal modulation scheme of16 QAM and 18 QAM for channel E (channel B).

The transmitter and the receiver may be a wireless transmit/receive unit(WTRU) or a base station. The terminology “WTRU” includes but is notlimited to a user equipment (UE), a mobile station, a fixed or mobilesubscriber unit, a pager, a cellular telephone, a personal digitalassistant (PDA), a computer, or any other type of user device capable ofoperating in a wireless environment. The terminology “base station”includes but is not limited to a Node-B, a site controller, an accesspoint (AP), or any other type of interfacing device capable of operatingin a wireless environment.

Although the features and elements of the present invention aredescribed in the preferred embodiments in particular combinations, eachfeature or element can be used alone without the other features andelements of the preferred embodiments or in various combinations with orwithout other features and elements of the present invention. Themethods or flow charts provide in the present invention may beimplemented in a computer program, software, or firmware tangiblyembodied in a computer-readable storage medium for execution by ageneral purpose computer or a processor. Examples of computer-readablestorage mediums include a read only memory (ROM), a random access memory(RAM), a register, cache memory, semiconductor memory devices, magneticmedia such as internal hard disks and removable disks, magneto-opticalmedia, and optical media, such as CD-ROM disks, and digital versatiledisks (DVDs).

Suitable processors include, by way of example, a general purposeprocessor, a special purpose processor, a conventional processor, adigital signal processor (DSP), a plurality of microprocessors, one ormore microprocessors in association with a DSP core, a controller, amicrocontroller, Application Specific Integrated Circuits (ASICs), FieldProgrammable Gate Arrays (FPGAs) circuits, any other type of integratedcircuit (IC), and/or a state machine.

A processor in association with software may be used to implement aradio frequency transceiver for use in a wireless transmit receive unit(WTRU), user equipment (UE), terminal, base station, radio networkcontroller (RNC), or any host computer. The WTRU may be used inconjunction with modules, implemented in hardware and/or software, suchas a camera, a video camera module, a videophone, a speakerphone, avibration device, a speaker, a microphone, a television transceiver, ahands free headset, a keyboard, a Bluetooth® module, a frequencymodulated (FM) radio unit, a liquid crystal display (LCD) display unit,an organic light-emitting diode (OLED) display unit, a digital musicplayer, a media player, a video game player module, an Internet browser,and/or any wireless local area network (WLAN) module.

What is claimed is:
 1. A method for transmitting multiple data streamsin an Institute of Electrical and Electronics Engineers (IEEE) 802.11device, the method comprising: generating a first spatial stream and asecond spatial stream; on a condition that the first spatial stream andthe second spatial stream belong to a first station (STA): processingeach of the first spatial stream and the second spatial stream togenerate two or more space-time streams, mapping the space-time streamsassociated with the first STA to a plurality of data streams, andtransmitting the plurality of data streams via a plurality of antennasto the first STA; on a condition that the first spatial stream belongsto a first STA and the second spatial stream belongs to a second STA:processing the first spatial stream to generate a first set of two ormore space-time streams and the second spatial stream to generate asecond set of two or more space-time streams, mapping the first set ofspace-time streams and the second set of space-time streams to aplurality of data streams, and transmitting the data streams via aplurality of antennas to the first STA and the second STA.
 2. The methodof claim 1, wherein the space-time streams are generated by using one ormore of a space time block coding (STBC) processing or a cyclic delaydiversity (CDD) processing.
 3. The method of claim 1 comprisingreceiving a V matrix, wherein the processor is configured to receive a Vmatrix, wherein the V matrix is a unitary matrix derived from singularvalue decomposition (SVD) of an estimated channel matrix, and whereinthe V matrix is associated with a STA and a sub carrier.
 4. The methodof claim 3, wherein the processing of the spatial streams or the mappingof the space-time streams is performed based on the received V matrix.5. The method of claim 3 wherein the V matrix is a feedback matrix. 6.The method of claim 4, wherein the feedback matrix is associated with achannel state information (CSI).
 7. An Institute of Electrical andElectronics Engineers (IEEE) 802.11 device comprising: a processor and amemory having stored therein executable instructions for execution bythe processor to at least: generate a first spatial stream and a secondspatial stream; on a condition that the first spatial stream and thesecond spatial stream belong to a first station (STA): process each ofthe first spatial stream and the second spatial stream to generate twoor more space-time streams, map the space-time streams associated withthe first STA to a plurality of data streams, and transmit the pluralityof data streams via a plurality of antennas to the first STA; on acondition that the first spatial stream belongs to a first STA and thesecond spatial stream belongs to a second STA: process the first spatialstream to generate a first set of two or more space-time streams and thesecond spatial stream to generate a second set of two or more space-timestreams, map the first set of space-time streams and the second set ofspace-time streams to a plurality of data streams, and transmit the datastreams via a plurality of antennas to the first STA and the second STA.8. The IEEE 802.11 device of claim 7, wherein the space-time streams aregenerated by using one or more of a space time block coding (STBC)processing or a cyclic delay diversity (CDD) processing.
 9. The IEEE802.11 device of claim 7, wherein the processor is configured to receivea V matrix, wherein the V matrix is a unitary matrix derived fromsingular value decomposition (SVD) of an estimated channel matrix, andwherein the V matrix is associated with a STA and a sub carrier.
 10. TheIEEE 802.11 device of claim 9, wherein the processing of the spatialstreams or the mapping of the space-time streams is performed based onthe received V matrix.
 11. The IEEE 802.11 device of claim 9, whereinthe V matrix is a feedback matrix.
 12. The IEEE 802.11 device of claim11, wherein the feedback matrix is associated with a channel stateinformation (CSI).